Prediksi Tinggi Gelombang dan Kecepatan Angin di Pantai Menggunakan Metode BiGRU
DOI:
https://doi.org/10.21111/fij.v10i1.13018Abstract
Abstrak Indonesia terletak di antara Samudera Pasifik dan Samudera Hindia yang membuat Indonesia menjadi pusat jalur perdagangan internasional. Pada lokasi desa Karangduwur yang berlokasi di Jawa Tengah memiliki potensi ekonomi maritim yang kuat tetapi juga memiliki risiko cuaca yang besar juga. Oleh karena itu tujuan dari penelitian ini yaitu untuk memprediksi tinggi gelombang dan kecepatan angin.   Metode prediksi yang digunakan pada penelitian kali ini adalah BiGRU (Bidirectional Gated Recurrent Unit) karena BiGRU memiliki hasil prediksi yang baik dibanding metode deep learning yang lain. Penelitian ini menggunakan data time series    yang berisi data tinggi gelombang dan kecepatan angin. Data unsur cuaca diambil per 12 jam dari bulan Januari 2021 – bulan April 2024. Metode BiGRU dapat digunakan dalam memprediksi cuaca maritim dengan fungsi aktivasi paling optimal untuk prediksi tinggi gelombang dan kecepatan angin ialah Relu, serta untuk prediksi tinggi gelombang dan kecepatan angin memiliki jumlah Batch Size yang optimal terdapat pada Batch Size 16. Dengan hasil nilai MAPE untuk prediksi ketinggian gelombang sebesar 1.6434% dan untuk prediksi kecepatan angin sebesar 0.6560%. Nilai MAPE pada model BiGRU memiliki nilai yang kecil dimana kurang dari 10% maka model BiGRU dikatakan sangat baik untuk prediksi pada data cuaca maritim. Kata kunci: Cuaca, Kecepetan angin, Tinggi gelombang, BiGRU  Abstract [Prediction of Wave Height and Wind Speed ​​on the Coast Using the BiGRU Method] Indonesia is located between the Pacific Ocean and the Indian Ocean, which makes it the center of international trade routes. Karangduwur village, located in Central Java, has strong maritime economic potential but also has great weather risks. Therefore, the purpose of this research is to predict wave height and wind speed.  The prediction method used in this research is BiGRU (Bidirectional Gated Recurrent Unit) because BiGRU has good prediction results compared to other deep learning methods. This research uses time series data containing wave height and wind speed data. Weather element data is taken per 12 hours from January 2021 - April 2024. The BiGRU method can be used in predicting maritime weather with the most optimal activation function for predicting wave height and wind speed is Relu, and for predicting wave height and wind speed, the optimal number of Batch Size is Batch Size 16. With the results of the MAPE value for wave height prediction of 1.6434% and for wind speed prediction of 0.6560%. The MAPE value in the BiGRU model has a small value which is less than 10%, so the BiGRU model is said to be very good for prediction on maritime weather data. Keywords: Weather, Wind speed, Wave height, BiGRUDownloads
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